Numerous mining and mineral processing activities require adjustments that are or could be based on visual observations or physical sampling of the particle size or size distribution of the ores involved. For example, mine blasting parameters can be adjusted using a size measurement of the feed into a primary crusher. Further, crusher settings can be controlled by measurement of the crusher discharge and autogenous mill loading can be optimized by measurement of the mill feed. In addition, an agglomeration circuit may be controlled by measurement of the pellet product, recycled undersize, or material in a pelletizing drum.
One principal prior art method for providing size distribution measurements involves using an automated or manual sampling procedure. Analyzing a physical sample is often not practical in the settings referred to above since the samples must be taken to a laboratory for screen sieve analysis to determine the size of the particles in the sample. Further, even automated procedures (e.g., wherein a robotic arm is used to take the samples) do not overcome the basic difficulty of obtaining a sample because of the inaccessibility or size of the ore (e.g., in situations where trains dump mine run ore containing pieces weighing in excess of a ton).
Personal visual observation is a second principal method of determining particle size and size distribution, and has advantages and disadvantages. In this regard, while advantages of visual observation include speed, non-obtrusiveness, and the ability to make determinations with respect to many different parameters, these advantages are outweighed in the many applications by subjective nature of the observation, the possibility of human error, the missing of events due to lack of vigilance, and the limited response time of a human observer.
Recent advances in digital computers, in combination with television technology, have enabled human vision to be mimicked by digital computers. Existing computer vision systems are typically based on interpretations of one dimensional pictures such as that provided by a single line scan. This reliance on one dimensional pictures creates problems with incorrectly interpreting coarsely textured, irregular shaped and layered pieces or particles of ore. A discussion of the use of computer vision systems in determining the sizes of ore particles traveling along a conveyor belt or the like is provided in Grannes et al., "Development of a Digital Image Based On-Line Product Size Sensor for Taconite Mining" Tenth WVU International Mining Electrotechnology Conf., pp. 102-109 (July 1990).
A number of patents disclose the use of digital computers to interpret surface information gathered by a camera. Some of these patents, e.g., U.S. Pat. Nos. 4,660,086 (Lemelson) and 5,023,714 (Lemelson), disclose automatic scanning apparatus and methods for inspecting images. The apparatus comprises a camera which outputs an image signal of a viewed object to a computer. The computer then compares the shape of the scanned object with that of the images stored in memory in order to identify the object.
U.S. Pat. No. 4,916,640 (Gasperi et al ) discloses a video image processing system which evaluates characteristics of an object within a video image. The processing system comprises two cameras for recording images, a programmable controller for receiving the images from the cameras and for determining whether parameters from the picture fall within a given tolerance range, and a programming terminal for providing commands to the programmable controller.
U.S. Pat. No. 4,377,340 (Green et al) discloses a method and apparatus for detecting impurities on the surface of a semiconductor wafer. The apparatus comprises a collimated light source, a camera and an image processor. In operation, the collimated light is directed upon the wafer and the camera receives the scattered light from the surface of the wafer. The intensity of the received light is compared with a calibrated model to determine the size of a particle located on the wafer.
U.S. Pat. No. 4,121,294 (Galanis et al.) discloses an electro-optical gaging system comprising a camera, a digital computer for receiving and processing images from the camera, and a control system which receives commands from the computer for controlling the shape of a hot metallic bar.